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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Environmental Physiology at the Johnson Space Center: Past, Present, and Future

This viewgraph presentation reviews the work in environmental physiology done at Johnson Space Center (JSC). The work is aimed at keeping astronauts healthy. This is a different approach than treating the sick, and is more of an occupational health model. The reduction of risks is the main emphasis for this work. They emphasis is to reduce the risk of decompression sickness (DCS) and acute mountain sickness (AMS). The work in environmental physiology encompasses the following areas: (1) Pressure: hypobaric and hyperbaric (2) Gases: hypoxia and hyperoxia, hypercapnia--closed space issues, inert gas physiology / respiration (3) Temperature: hypothermia and hyperthermia, thermal comfort, Protective clothing diving, aviation, mountaineering, and space (4) Acceleration (5) Noise and Vibration (6) Exercise / Performance (6) Acclimatization / Adaptation: engineering solutions when necessary. This presentation reviews the work done at JSC in the areas of DCS and AMS.

Conkin, Johnny↗
NASA NTRS2009

Human Research Program (HRP) Exploration Medical Capability (ExMC) Standing Review Panel (SRP)

The SRP believes strongly that regularly performed in-flight crew assessments are needed in order to identify a change in health status before a medical condition becomes clinically apparent. It is this early recognition in change that constitutes the foundation of the "occupational health model" expounded in the HRP Requirements Document as a key component of the HRP risk mitigation strategy that will enable its objective of "prevention and mitigation of human health and performance risks". A regular crew status examination of physiological and clinical performance is needed. This can be accomplished through instrumented monitoring of routine embedded tasks. The SRP recommends addition of a new gap to address this action under Category 3.0 Mitigate the Risk. This new gap is closely associated with Task 4.19 which addresses the lack of adequate biomedical monitoring capabilities for performing periodic clinical status evaluations and contingency medical monitoring. A corollary to these gaps is the critical emphasis on preventive medicine, not only during pre- and post-flight phases of a mission as is the current practice, but continued into the in-flight phases of exploration class missions.

Cintron, Nitza↗
NASA NTRS2010

Crash Test of an MD-500 Helicopter with a Deployable Energy Absorber Concept

On December 2, 2009, a full scale crash test was successfully conducted of a MD-500 helicopter at the NASA Langley Research Center Landing and Impact Research Facility . The purpose of this test was to evaluate a novel composite honeycomb deployable energy absorbing (DEA) concept for attenuation of structural and crew loads during helicopter crashes under realistic crash conditions. The DEA concept is an alternative to external airbags, and absorbs impact energy through crushing. In the test, the helicopter impacted the concrete surface with 11.83 m/s (38.8 ft/s) horizontal, 7.80 m/s (25.6 ft/s) vertical and 0.15 m/s (0.5 ft/s) lateral velocities; corresponding to a resultant velocity of 14.2 m/s (46.5 ft/s). The airframe and skid gear were instrumented with accelerometers and strain gages to determine structural integrity and load attenuation, while the skin of the airframe was covered with targets for use by photogrammetry to record gross vehicle motion before, during, and after the impact. Along with the collection of airframe data, one Hybrid III 50th percentile anthropomorphic test device (ATD), two Hybrid II 50th percentile ATDs and a specialized human surrogate torso model (HSTM) occupant were seated in the airframe and instrumented for the collection of occupant loads. Resultant occupant data showed that by using the DEA, the loads on the Hybrid II and Hybrid III ATDs were in the Low Risk regime for the injury criteria, while structural data showed the airframe retained its structural integrity post crash. Preliminary results show that the DEA is a viable concept for the attenuation of impact loads.

Littell, Justin D.↗
NASA NTRS2011

Astronaut Medical Selection and Flight Medicine Care During the Shuttle ERA 1981 to 2011

The NASA Shuttle Program began with congressional budget approval in January 5, 1972 and the launch of STS-1 on April 12, 1981 and recently concluded with the landing of STS-135 on July 21, 2011. The evolution of the medical standards and care of the Shuttle Era Astronauts began in 1959 with the first Astronaut selection. The first set of NASA minimal medical standards were documented in 1977 and based on Air Force, Navy, Department of Defense, and the Federal Aviation Administration standards. Many milestones were achieved over the 30 years from 1977 to 2007 and the subsequent 13 Astronaut selections and 4 major expert panel reviews performed by the NASA Flight Medicine Clinic, Aerospace Medicine Board, and Medical Policy Board. These milestones of aerospace medicine standards, evaluations, and clinical care encompassed the disciplines of preventive, occupational, and primary care medicine and will be presented. The screening and retention standards, testing, and specialist evaluations evolved through periodic expert reviews, evidence based medicine, and Astronaut medical care experience. The last decade of the Shuttle Program saw the development of the International Space Station (ISS) with further Space medicine collaboration and knowledge gained from our International Partners (IP) from Russia, Canada, Japan, and the European Space Agencies. The Shuttle Program contribution to the development and implementation of NASA and IP standards and waiver guide documents, longitudinal data collection, and occupational surveillance models will be presented along with lessons learned and recommendations for future vehicles and missions.

Johnston, S.↗
DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗
DOE OSTI2021

A framework for estimating the energy-saving potential of occupant behaviour improvement

Energy-related occupant behaviour in buildings has demonstrated considerable energy-saving potential. However, the current modelling method of occupant behaviour does not give sufficient considerations on the implementation difficulty of behaviour and provide a holistic map from survey data to various behaviour models. This article proposes a holistic survey-and-simulation-based framework for estimating the energy-saving potential of occupant behaviour improvement. In the framework, seven typical categories of occupant behaviour models are identified based on the survey results. According to the implementation difficulty, the models are integrated into four behaviour styles (baseline, wasteful, moderate and austere) to represent different levels of energy-saving consciousness of occupants. Based on a case study with a nationwide survey in Singapore, there are remarkable energy savings potential if occupant behaviour is improved; the building energy consumption can be reduced by up to 9.5% with the moderate behaviour improvement, and up to 21.0% with the aggressive behaviour improvement. The simulation results accord well with the measured results within a reasonable range of deviation. The framework can be applied to estimate the energy-saving potential of occupant behaviour improvement in a building with affordable cost, and the findings can inform a behaviour improvement programme with effective and efficient measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2015

NASA Astronaut Occupational Surveillance Program and Lifetime Surveillance of Astronaut Health, LSAH, Astronaut Exposures and Risk in the Terrestrial and Spaceflight Environment

United States Astronauts have a very unique occupational exposure profile. In order to understand these risks and properly address them, the National Aeronautics and Atmospheric Administration, NASA, originally created the Longitudinal Study of Astronaut Health, LSAH. The first LSAH was designed to address a variety of needs regarding astronaut health and included a 3 to 1 terrestrial control population in order to compare United States "earth normal" disease and aging to that of a microgravity exposed astronaut. Over the years that program has been modified, now termed Lifetime Surveillance of Astronaut Health, still LSAH. Astronaut spaceflight exposures have also changed, with the move from short duration shuttle flights to long duration stays on international space station and considerable terrestrial training activities. This new LSAH incorporates more of an occupational health and medicine model to the study of occupationally exposed astronauts. The presentation outlines the baseline exposures and monitoring of the astronaut population to exposures, both terrestrial, and in space.

Keprta, Sean R.↗
DOE OSTI2025

Impact of microkinetic modeling assumptions on predicted kinetics and mechanisms over undercoordinated sites

Accurate modeling of catalytic reactions on undercoordinated sites requires accounting for the structural and ensemble-specific nature of the active sites. This study examines how common microkinetic modeling (MKM) assumptions affect predicted kinetics and mechanisms on the stepped Pt(211) facet for the ethane dehydrogenation (EDH) and the ethane hydrogenolysis (EH). Six (211) MKMs were developed, differing in (i) the number of active sites represented, (ii) adsorbate site occupancy treatment, and (iii) inclusion of cross-facet interactions. These models are benchmarked against a particle-based microkinetic model (PB-MKM), which best represents step-edge behavior. MKM assumptions caused deviations in turnover frequencies exceeding ten orders of magnitude and led to contrasting mechanistic and selectivity predictions. Multi-site MKMs overestimate activity by inflating free site availability, single-site models underestimate activity, and uniform occupancy models overpredict coverage of multi-dentate intermediates, leading to reaction-specific artifacts. Overall, the Combined Site Edge Model (CSEM), a single-site MKM accounting for site occupancy and cross-facet interactions, most closely approximates PB-MKM predictions. All models predict similar kinetics when surfaces are clean or primarily occupied by monodentate species. This work provides practical guidance for selecting MKM frameworks for undercoordinated catalytic surfaces and highlights the critical role of modeling assumptions in catalytic predictions.

(211) facet↗
DOE OSTI2026

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump↗
NASA NTRSDate not supplied

Comparison of Anthropomorphic Test Device and human Volunteer Responses in Landing Impact Tests of U.S. Space Vehicles

United States (U.S.) crewed vehicles are being designed to support the National Aeronautics and Space Administration’s (NASA’s) human spaceflight programs. Vehicles must be designed to meet NASA’s occupant protection requirements including landing injury assessment with anthropomorphic test devices (ATDs) and analytical models. However, these tools are limited in capturing all injuries that might occur during spacecraft landings. A NASA study of injuries during Soyuz vehicle landings has shown that analytical models are underpredicting occupant injury. Because of the inherent limitations with our analytical tools, human volunteer impact testing was employed to validate the safety of U.S. crewed vehicles. A total of 84 human volunteer tests in 11 different test orientations and g-levels were completed as part of this effort in collaboration with the Air Force Research Laboratory (AFRL) at Wright-Patterson Air Force Base and the vehicle development companies. Human subjects were tested at various realistic landing loads and in the highest fidelity seat and suit components that were available at the time of testing for two U.S. vehicles. Matched-pair ATD tests in the same test conditions were also conducted with small female and midsized male Hybrid III ATDs. ATDs were fully instrumented. Head accelerations and subjective responses were recorded in human subjects. In some cases, chest accelerations were captured. Responses of the ATDs and humans in matched-pair tests were compared. No ATD tests showed evidence for risk of injury based on NASA occupant protection requirements. Human subjects reported 17 cases of discomfort or pain, 1 human subject was diagnosed with a minor injury that was not evident in the ATD tests. These results provide evidence that ATDs do not capture all potential injury risks, namely lower severity injuries, discomfort, pain, and fit issues. Overall, human testing is beneficial to understanding the true risk of injury to crewmembers during Earth landings.

Teresa Reiber↗
NASA NTRS2024

Comparison of Anthropomorphic Test Device and Human Volunteer Responses in Simulated Landing Impact Tests of U.S. Space Vehicles

United States (U.S.) crewed vehicles are being designed to support the National Aeronautics and Space Administration’s (NASA’s) human spaceflight programs. Vehicles must be designed to meet NASA’s occupant protection requirements including landing injury assessment with anthropomorphic test devices (ATDs) and analytical models. However, these tools are limited in capturing all injuries that might occur during spacecraft landings. A NASA study of injuries during Soyuz vehicle landings has shown that analytical models are underpredicting occupant injury. Because of the inherent limitations with our analytical tools, human volunteer impact testing was employed to assess flight-like landing conditions of U.S. crewed vehicles. A total of 84 human volunteer tests in 11 different test orientations and g-levels were completed as part of this effort in collaboration with the Air Force Research Laboratory (AFRL) at Wright-Patterson Air Force Base and U.S. vehicle development companies. Human subjects were tested at various realistic landing loads and in the highest fidelity seat and suit components that were available at the time of testing for two U.S. vehicles. Matched-pair ATD tests in the same test conditions were also conducted with small female and midsized male Hybrid III ATDs. ATDs were fully instrumented. Head accelerations and subjective responses were recorded for human subjects. In some cases, chest accelerations were captured. Responses of the ATDs and humans in matched-pair tests were compared. No ATD tests showed evidence for risk of injury based on NASA occupant protection requirements. Human subjects reported 17 cases of discomfort or pain, and 1 human subject was diagnosed with a minor injury that was not evident in the ATD tests. These results provide evidence that ATDs do not capture all potential injury risks, namely lower severity injuries, discomfort, pain, and fit issues. Overall, human testing is beneficial to understanding the true risk of injury to crewmembers during Earth landings.

Teresa M Reiber↗
NASA NTRS2024

Comparison of Anthropomorphic Test Device and Human Volunteer Responses in Simulated Landing Impact Tests of U.S. Space Vehicles

United States (U.S.) crewed vehicles are being designed to support the National Aeronautics and Space Administration’s (NASA’s) human spaceflight programs. Vehicles must be designed to meet NASA’s occupant protection requirements including landing injury assessment with anthropomorphic test devices (ATDs) and analytical models. However, these tools are limited in capturing all injuries that might occur during spacecraft landings. A NASA study of injuries during Soyuz vehicle landings has shown that analytical models are underpredicting occupant injury. Because of the inherent limitations with our analytical tools, human volunteer impact testing was employed to assess flight-like landing conditions of U.S. crewed vehicles. A total of 84 human volunteer tests in 11 different test orientations and g-levels were completed as part of this effort in collaboration with the Air Force Research Laboratory (AFRL) at Wright-Patterson Air Force Base and U.S. vehicle development companies. Human subjects were tested at various realistic landing loads and in the highest fidelity seat and suit components that were available at the time of testing for two U.S. vehicles. Matched-pair ATD tests in the same test conditions were also conducted with small female and midsized male Hybrid III ATDs. ATDs were fully instrumented. Head accelerations and subjective responses were recorded for human subjects. In some cases, chest accelerations were captured. Responses of the ATDs and humans in matched-pair tests were compared. No ATD tests showed evidence for risk of injury based on NASA occupant protection requirements. Human subjects reported 17 cases of discomfort or pain, and 1 human subject was diagnosed with a minor injury that was not evident in the ATD tests. These results provide evidence that ATDs do not capture all potential injury risks, namely lower severity injuries, discomfort, pain, and fit issues. Overall, human testing is beneficial to understanding the true risk of injury to crewmembers during Earth landings.

Teresa M Reiber↗
NASA NTRSDate not supplied

Comparison of Anthropomorphic Test Device and Human Volunteer Responses in Simulated Landing Impact Tests of U.S. Space Vehicles

United States (U.S.) crewed vehicles are being designed to support the National Aeronautics and Space Administration’s (NASA’s) human spaceflight programs. Vehicles must be designed to meet NASA’s occupant protection requirements including landing injury assessment with anthropomorphic test devices (ATDs) and analytical models. However, these tools are limited in capturing all injuries that might occur during spacecraft landings. A NASA study of injuries during Soyuz vehicle landings has shown that analytical models are underpredicting occupant injury. Because of the inherent limitations with our analytical tools, human volunteer impact testing was employed to assess flight-like landing conditions of U.S. crewed vehicles. A total of 84 human volunteer tests in 11 different test orientations and g-levels were completed as part of this effort in collaboration with the Air Force Research Laboratory (AFRL) at Wright-Patterson Air Force Base and U.S. vehicle development companies. Human subjects were tested at various realistic landing loads and in the highest fidelity seat and suit components that were available at the time of testing for two U.S. vehicles. Matched-pair ATD tests in the same test conditions were also conducted with small female and midsized male Hybrid III ATDs. ATDs were fully instrumented. Head accelerations and subjective responses were recorded for human subjects. In some cases, chest accelerations were captured. Responses of the ATDs and humans in matched-pair tests were compared. No ATD tests showed evidence for risk of injury based on NASA occupant protection requirements. Human subjects reported 17 cases of discomfort or pain, and 1 human subject was diagnosed with a minor injury that was not evident in the ATD tests. These results provide evidence that ATDs do not capture all potential injury risks, namely lower severity injuries, discomfort, pain, and fit issues. Overall, human testing is beneficial to understanding the true risk of injury to crewmembers during Earth landings.

Teresa M Reiber↗
DOE OSTI2022

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Leveraging Fine-Grained Occupancy Estimation Patterns for Effective HVAC Control

As occupancy sensing technologies become mature, various occupancy sensors are increasingly deployed in commercial buildings for pervasive occupancy monitoring. These sensors provide occupant-count data, which contains rich spatiotemporal information about occupancy patterns. With long-term occupant-count data collected from a commercial building, we design three different predictive models that capture the occupancy dynamics and examine how a model predictive control of the HVAC system benefits from actual occupancy count prediction. Our analysis reveals that mispredictions of occupancy states, especially false positives and false negatives, may introduce inefficient control that leads to energy waste or user discomfort. To address this issue, we take a step further to design an adaptive model predictive controller that minimizes inefficient control actions according to misprediction types and distributions. A comprehensive evaluation is performed in OpenBuild and EnergyPlus simulators to study the effectiveness of the proposed end-to-end control strategy. The evaluation shows that the proposed solution reduces energy consumption by 29.5% while improving the average weighted occupants comfort by 86.7% in Predicted Mean Vote (PMV) over the fixed schedule strategy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Hardware-Based Emulator with Deep Learning Model for Building Energy Control and Prediction Based on Occupancy Sensors’ Data

Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typical cyber-physical system (CPS). In this paper, we aim to build a hardware-based emulation platform to study the occupancy data’s features, which can be further extracted by using machine learning models. In particular, we propose two hardware-based emulators to investigate the use of wired/wireless communication interfaces for occupancy sensor-based building CPS control, and the use of deep learning to predict the building energy consumption with the sensor data. We hypothesize is that the building energy consumption may be predicted by using the occupancy data collected by the sensors, and question what type of prediction model should be used to accurately predict the energy load. Another hypothesis is that an in-lab hardware/software platform could be built to emulate the occupancy sensing process. The machine learning algorithms can then be used to analyze the energy load based on the sensing data. To test the emulator, the occupancy data from the sensors is used to predict energy consumption. The synchronization scheme between sensors and the HVAC server will be discussed. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies, and used an enhanced deep learning model—which has sequence-to-sequence long short-term memory (Seq2Seq LSTM)—with an attention model to predict the building energy consumption with the preservation of the intrinsic patterns. Because the long-range temporal dependencies are captured, the Seq2Seq models may provide a higher accuracy by using LSTM architectures with encoder and decoder. Meanwhile, LSTMs can capture the temporal and spatial patterns of time series data. The attention model can highlight the most relevant input information in the energy prediction by allocating the attention weights. The communication overhead between the sensors and the HVAC control server can also be alleviated via the attention mechanism, which can automatically ignore the irrelevant information and amplify the relevant information during CNN training. Our experiments and performance analysis show that, compared with the traditional LSTM neural network, the performance of the proposed method has a 30% higher prediction accuracy.

Ye, Zhijing↗
DOE OSTI2022

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗